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The benefit of regular physical activity and exercise training for the prevention of cardiovascular and metabolic diseases is undisputed. Many molecular mechanisms mediating exercise effects have been deciphered. Personalised exercise prescription can help patients in achieving their individual greatest benefit from an exercise-based cardiovascular rehabilitation programme. Yet, we still struggle to provide truly personalised exercise prescriptions to our patients. In this position paper, we address novel basic and translational research concepts that can help us understand the principles underlying the inter-individual differences in the response to exercise, and identify early on who would most likely benefit from which exercise intervention. This includes hereditary, non-hereditary and sex-specific concepts. Recent insights have helped us to take on a more holistic view, integrating exercise-mediated molecular mechanisms with those influenced by metabolism and immunity. Unfortunately, while the outline is recognisable, many details are still lacking to turn the understanding of a concept into a roadmap ready to be used in clinical routine. This position paper therefore also investigates perspectives on how the advent of ‘big data’ and the use of animal models could help unravel inter-individual responses to exercise parameters and thus influence hypothesis-building for translational research in exercise-based cardiovascular rehabilitation.
Aims
Averaged measurements, but not the progression based on multiple assessments of carotid intima-media thickness, (cIMT) are predictive of cardiovascular disease (CVD) events in individuals. Whether this is true for conventional risk factors is unclear.
Methods and results
An individual participant meta-analysis was used to associate the annualised progression of systolic blood pressure, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol with future cardiovascular disease risk in 13 prospective cohort studies of the PROG-IMT collaboration (n = 34,072). Follow-up data included information on a combined cardiovascular disease endpoint of myocardial infarction, stroke, or vascular death. In secondary analyses, annualised progression was replaced with average. Log hazard ratios per standard deviation difference were pooled across studies by a random effects meta-analysis. In primary analysis, the annualised progression of total cholesterol was marginally related to a higher cardiovascular disease risk (hazard ratio (HR) 1.04, 95% confidence interval (CI) 1.00 to 1.07). The annualised progression of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol was not associated with future cardiovascular disease risk. In secondary analysis, average systolic blood pressure (HR 1.20 95% CI 1.11 to 1.29) and low-density lipoprotein cholesterol (HR 1.09, 95% CI 1.02 to 1.16) were related to a greater, while high-density lipoprotein cholesterol (HR 0.92, 95% CI 0.88 to 0.97) was related to a lower risk of future cardiovascular disease events.
Conclusion
Averaged measurements of systolic blood pressure, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol displayed significant linear relationships with the risk of future cardiovascular disease events. However, there was no clear association between the annualised progression of these conventional risk factors in individuals with the risk of future clinical endpoints.